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Question
Carlos Cavazos, Director of Human Resources, is exploring employee absenteeism at the Plano Piano Plant. A multiple regression analysis was performed using the following variables. The results are presented below.| Variable | Description |
| Y | number of days absent last fiscal year |
| x1 | commuting distance (in miles) |
| x2 | employee's age (in years) |
| x3 | single-parent household (0 = yes, 1 = no) |
| x4 | length of employment at PPP (in years) |
| x5 | shift (0 = day, 1 = night) |
| Coefficients | Standard Error | t Statistic | p-value | |
| Intercept | 6.594146 | 3.273005 | 2.014707 | 0.047671 |
| x1 | -0.18019 | 0.141949 | -1.26939 | 0.208391 |
| x2 | 0.268156 | 0.260643 | 1.028828 | 0.307005 |
| x3 | -2.31068 | 0.962056 | -2.40182 | 0.018896 |
| x4 | -0.50579 | 0.270872 | -1.86725 | 0.065937 |
| x5 | 2.329513 | 0.940321 | 2.47736 | 0.015584 |
| df | SS | MS | F | p-value | |
| Regression | 5 | 279.358 | 55.8716 | 4.423755 | 0.001532 |
| Residual | 67 | 846.2036 | 12.6299 | ||
| Total | 72 | 1125.562 |
| R = 0.498191 | R2 = 0.248194 | Adj R2 = 0.192089 |
| se = 3.553858 | n = 73 |
Which of the following conclusions can be drawn from the above results?
a) All the independent variables in the regression are significant at 5% level.
b) Commuting distance is a highly significant (<1%) variable in explaining absenteeism.
c) Age of the employees tends to have a very significant (<1%) effect on absenteeism.
d) This model explains a little over 49% of the variability in absenteeism data.
e) A single-parent household employee is expected to be absent less number of days all other variables held constant compared to one who is not a single-parent household.
Answer
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